Usually, in mobile wireless communication, a transmitter sends a signal as shown in FIG. 6. That is, a wireless signal includes a training sequence 10, a header 20, and data 30. Upon reception of a wireless signal of this type, a receiver establishes synchronization with the wireless signal by using a carrier frequency or some other parameters, and calculates and sets tap coefficients etc. (an adaptive operation by an adaptive algorithm) of its own equalization filter (also called "adaptive filter") by using the training sequence 10 to eliminate influences of intersymbol interference. Once the tap coefficients of the equalization filter are set, influences of intersymbol interference can be eliminated; therefore, it becomes possible to receive data contained in the header 20 and the data 30 that follow the training sequence 10. The header 20 contains control information for the data 30 and other information, and the data 30 is the content to be sent from the transmitter to the receiver.
As described above, the tap coefficients of the equalization filter are set by using the training sequence 10. However, this does not mean that it is not necessary to perform any correcting operations during subsequent reception of the header 20 and the data 30. That is, even in a room, the state of a transmission path (propagation characteristics) is varied by, for instance, movement of a person at a slower rate than a symbol rate (data transmission rate). When the propagation characteristics vary in this manner, the tap coefficients of the equalization filter need to be varied accordingly. Therefore, calculation for updating the tap coefficients of the equalization filter is performed even during reception of the header 20 and the data 30. But the volume of this calculation is enormous. For example, where a recursive least square (RLS) algorithm, which is considered a high-convergence, stable adaptive algorithm, in complex number form, k(7k+6) times of multiplications are needed for k-stage filter taps. If k is 7 and the symbol rate is 10 MHz, a computing ability of 3.85 GIPS is needed. In practice, it is problematic to perform such calculation during reception of the header 20 and the data 30, and even the training sequence 10.
Therefore, as a realistic measure, an adaptive algorithm that is poor in characteristics but simple is used, or high-speed sampling is performed and a head portion of symbols is used which is free of intersymbol interference. However, as the transmission rate increases, these techniques can no longer be accommodated and it becomes more necessary to use an algorithm, such as the RLS algorithm, that requires a very high computing ability.
To improve the convergence in executing an adaptive algorithm as mentioned above, it is better that data to be transmitted and received is whitened. "Whitened" means that it is flat over the entire frequency range. This is because if the adaptive operation is performed for the reception data having a deviation, tap coefficients may vary in an undesired direction to cause a reception error. Usually, the header 20 and the data 30 are also whitened by, for instance, scrambling that uses an LFSR (linear feedback shift register) or the like.
Published Unexamined Patent Application (PUPA) No. 7-162361 discloses use of an adaptive algorithm for the header 20 and the data 30 as mentioned above. However, this reference has no disclosure as to a signal-like nature of the header 20 and the data 30. PUPA No. 5-145452 discloses dividing a single, long unique word into a plurality of parts and inserting those into a data portion. This purpose is to synchronize with each data part by using each part of the unique word. In addition, usually a unique word has only a minimum necessary length because a long, redundant unique word decreases a data transmission amount. It is doubtful whether each part obtained by dividing a unique word into a plurality of parts in the manner as disclosed in the Published Unexamined PUPA No. 5-145452 has a certain meaning. Further, where divided parts are meaningful only as a whole, it is necessary to process a unique word after receiving the entire data, storing it in a buffer, receiving all the divided parts of the unique word, and setting tap coefficients.
As described above, there exists no effective method of reducing the calculation volume of tap coefficients tracking operation after tap coefficients of an equalization filter have been set by using a training sequence.